Usually running on the traditional business models, techniques and technologies, manufacturing companies are now gearing up fast to their digital journey. Not only have they made their business process digital now, they are also looking up how to gather data and make way to use the next-gen technology like AI and ML.SKF, a Swedish bearing and seal manufacturing company on its journey to reach manufacturing 4.0, is transforming its facilities to aid the growth.
“At SKF, the data is not just about us, it’s about helping our customers. Today data is a core business asset and the use of data and analytics is important in making better business decisions. For example, we want to leverage actionable, easy-to-use, and easily accessible data to predict and manage supply chain, so that customers can have the right product at the right time,” said Jaiveer Singh, IT Regional Manager APEC (Asia Pacific, excluding China)
SKF continues to invest in building cloud Data Warehouse capabilities i.e. Snowflake, Microsoft AZURE Arch data enabled services for data driven manufacturing approach. To enable SKF’s digitalization journey, it is adding new IT capabilities, technology platforms and actively educating people on having a data-first mindset.
Going forward, the company wants to leverage IoT to drive much higher levels of efficiency, significantly improved planned downtime, improved fleet and resource management, and optimized business operations. There will also be new levels of autonomy and control over how machines operate through data and insights.
Singh told ETCIO that for SKF, IIoT is about using real-time data from multiple sources and turning data into information so that action can be taken before anything happens. Action can mean to correct process parameters in real time, to tune the lubrication system, to order parts in advance and much more.
An example is SKF Insight – a wireless condition-based monitoring system for bearings that measures variables such as vibration levels and temperatures to spot anomalies at an early stage, reducing the need for unplanned downtime and stoppages. By combining integrated SKF Insight technologies with associated asset diagnostic and bearing health services, information relating to actual operating conditions is sent to cloud servers for remote diagnostics, enabling an understanding of the risk of future damage and failure.
SKF is gradually transforming its facilities to aid the growth of a ‘Future Factory’, aided by a well-defined strategic roadmap to reach Manufacturing 4.0 by 2023-2024. Company’s approach involves an incremental transformation of the supply chain, quality, engineering and people processes to achieve its goal of sustaining excellence across operations.
“At SKF we are currently working on connecting our processes – driving the digital transformation by integrating automation, software, and cutting-edge technologies. It Includes Predictive Cockpit (Condition monitoring) for maintenance, additive manufacturing for shop supplies, an AI-enabled Vision Inspection system supporting M2M & E2M connectivity, and a connected supply chain and full value chain to effectively manage and collaborate with supply chain partners,” Singh said.
The company has also successfully installed a Channel Monitoring System at its Pune factory for real-time equipment performance monitoring and a maintenance cockpit for real-time machine health monitoring. With access to real-time and remote monitoring, operators will be empowered to better predict and plan machine maintenance schedules, as well as develop long-term statistical evaluations of diagnostic data. Further, with the Equipment to Machine (E2M) connectivity project, it focuses on reducing scrap and man-machine intervention while improving built-in quality (BIQ).
“Also, our global acquisition, Presenso in AI, is a step forward in this direction. Presenso’s AI capability enables production plants to find and act on anomalies that were previously difficult to detect, automatically and without the need to employ data scientists. Within our manufacturing footprint, we are planning to utilize sensor technology, robotics, and SCADA system along with the control system of machines being upgraded to the latest PLC with advanced features,” he concluded
